期刊
JOURNAL OF BEHAVIORAL AND EXPERIMENTAL FINANCE
卷 41, 期 -, 页码 -出版社
ELSEVIER
DOI: 10.1016/j.jbef.2023.100860
关键词
Individual investor sentiment; Three-factor model; Chinese stock market; Social network; Text mining
This research examines the influence of individual investor sentiment derived from social networks on stock market returns. The study finds that individual investor sentiment has an independent impact on Chinese financial markets, and negative sentiment has a stronger effect on stock returns. Additionally, there is an asymmetric pattern in the relationship between sentiment and returns across different industry types.
This research explores the impact of individual investor sentiment derived from social networks on stock market returns. Using keyword-based techniques, we collect and analyze Sina Weibo posts related to COVID-19, extracting daily influential weighted sentiment indexes from a dataset of over 2.4 million posts in 2020. Empirical tests utilizing a sentiment-augmented three-factor model reveal that individual investor sentiment exerts an independent influence on Chinese financial markets, after controlling for market risk, size, and value effects. We further find that negative sentiment carries a stronger impact on stock returns, which is in line with the loss-averse behavior commonly observed among individual investors. We also find an asymmetric pattern in the sentiment-return relation across different industry types. While positive sentiment affects both types of industries that suffer or benefit from COVID-19, negative sentiment affects only the industries that suffer from the pandemic. Overall, our empirical results provide robust support for the significance of individual investor sentiment in explaining the behavior of the Chinese financial markets.
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